In unexpected emergency response scenarios, it is necessary to quickly obtain global situational images of the scene for subsequent assessment and decision-making. Swarm UAVs have the advantages of large number, low cost and fast imaging, and are widely used in military fields. This paper explores the application of swarm UAV cooperative reconnaissance to the field of emergency remote sensing, and constructs a swarm UAV remote sensing digital simulation and verification system, which researches and simulates and verifies the swarm UAV's formation coordination, airway planning, and cooperative splicing of multi-channel video. Aiming at the problem of unstable overlap rate between multiple video frames, an adaptive dynamic sampling algorithm is proposed to maintain the idempotence of the overall efficiency of the splicing algorithm under different overlap rates. Subsequently, for the unstable characteristics of video streams in response scenes, a breakpoint re-splicing algorithm is proposed to ensure that the availability of the algorithm can be maintained at the expense of splicing accuracy in poor shooting environments. The results show that: swarm UAVs can construct a global situational image of the scene in quasi real-time, and this paper can provide technical support for the application of swarm UAVs in the field of remote sensing in emergency response.